In the previous studies, this task is often modeled as a text classification problem. Then machine learning methods can be used to classify the source code's language type. For example, Khasnabish et al. [1]} used a Naive Bayesian classifier. Alrashedy et al. [2]} used a random forest classifier and XGBoost. Motivated by the research progress of neural text classification and code semantic learning [3]}, we propose a novel method DeepSCC by fine-tuning the pre-trained model RoBERTa [4]} to perform the source code classification task.
